This invention relates to a computer-based simulation model for simulating a transport system in an organism. More specifically, the present invention relates to a configurable simulation model that emulates the behavior of a circulatory system.
Almost all organisms have systems for channeling or otherwise controlling the movement of mass and/or energy in or around the organism. These systems are referred to herein as xe2x80x9cbio-transport systemsxe2x80x9d (BTS), and include, for example, circulatory systems, digestive (gastrointestinal) systems, pulmonary systems, lymphatic systems, renal systems, and the movement of chemical and biological entities within and among tissues and cells just to name a few.
One bio-transport system of particular interest herein is the circulatory system. The circulatory system channels blood and other entities through vessels and among the various organs to supply nutrients to tissues, to regulate body mechanisms, and to facilitate the flow of materials and interactions necessary in general to keep an organism alive. Additionally, the circulatory system contains a medium, that is, blood, in which various chemical, biological and physical reactions take place. Thus, the circulatory system is a complex system having geometric, physical and chemical/biological properties; flow behavior; internal reactions; and interactions among blood, vessels, connected organs, and the organism in general. The properties, configurations, behaviors, reactions and interactions of a bio-transport system are collectively referred to herein as xe2x80x9cbio-transport dynamicsxe2x80x9d [BTD].
As medicine becomes more quantitative, there is a need for analytic tools to relate more precisely causes to effects in organisms and to more clearly elucidate the mechanisms involved. This requires obtaining bio-transport dynamic data. For example, in the pharmaceutical field, there is a need to evaluate the effects of chemicals in drug studies by computing and displaying the concentration, at different points in the circulatory system and as a function of time, of a chemical injected into the body at a point in time and space, or bio-availability of an orally ingested drug in its journey through the GI tract and the circulatory system to its final destination at an organ or other target within the body. Aside from pharmaceutical applications, there is a need for analyzing bio-transport dynamics for diagnostic purposes, such as, when assigning a quantitative measure to the degree of atherosclerosis present in an individual""s specific circulatory system.
Despite the desire to analyze bio-transport dynamics of mass transport systems within organisms, the dynamic nature of these systems makes them inherently difficult to study. Conventional approaches of studying bio-transport dynamics of the circulatory system for example involve obtaining clinical measurements or images of the circulatory system in humans and animals. For example, blood pressure cuffs and direct pressure probes are used to measure flow rates and pressures, and ultrasound and angiography are used to image vessels of the circulatory system. These measurements and images are compared against norms to attempt to qualify an organism""s status and to help locate anomalies. Some of these tools are non-invasive but imprecise, such as sphygmomanometer, while others are precise but invasive, and potentially life threatening, such as cardiac catheterization.
Animal testing is another approach for obtaining bio-transport dynamic data that traditionally has allowed for more invasive measurements. Animal testing, however, is under scrutiny. Political and social pressure against animal testing has become very strong and is expected to increase. For example, scientists now must seek approval from the FDA for every primate subjected to experimentation and must account for every rat used. Animal testing is being framed today in a broader ethical context, and is likely to become even more circumscribed in the future.
Given the limitations presented by in-vivo testing, a theoretical approach in analyzing bio-transport dynamics is attractive. There are a number of practical difficulties, however, associated with a pure theoretical analysis of bio-transport dynamics that are not normally encountered outside living organisms. Sir James Lighthill [Lighthill M. J. Mathematical Biofluiddynamicsxe2x80x9d SIAM Regional Conference Series in Applied Math. 1975] lists four broad categories:
1. Unusual vessel distensability and resultant attenuation of wave propagation;
2. Great range of Reynolds numbers  greater than 5000 to  less than 100 with small capillaries  less than 10 microns;
3. Atypical fluid properties; and
4. Branching in lungs and circulatory system [20-30 forkings leading to  greater than 100 m branches].
To this list should be added the historic difficulty of obtaining clinical experimental data as mentioned above to compare with theory.
Piecemeal solutions that arise from considering only part of a problem-, or a radical simplification of the problem to obtain an assumption-restricted solution, while useful within the stipulated range of applicability, do not meet current and future clinical/research needs for scope, detail, accuracy and architecture. For example, in Guyton, et. al. xe2x80x9cComputer Analysis of Total Circulatory Function and of Cardiac Output Regulationxe2x80x9d, Chap. 17, Graphical, Algebraic and Computer Analyses 1973, a mathematical representation of the circulatory system is provided based on the system as a whole. Although such a model provides useful information on the circulatory system in gross terms, no detailed information with regard to spatial dependence of the system is available. In other words, this model can only provide data on bulk values for variables in the circulatory system and not for different components of the system where data tend to vary as suggested by Lighthill.
Therefore, a need exists for an approach that will enable researchers and physicians to experiment and practice with a bio-transport system without the attendant time constraints, risks and difficulties of dealing with a real bio-transport system in a living organism. The present invention fulfills this need among others.
The present invention provides an approach for analyzing bio-transport dynamics that overcomes the above-identified problems by simulating, in silico, a bio-transport system of an organism using a configurable simulation model. The configurable simulation model provides a generic framework that is readily customizable to simulate one or more bio-transport dynamics aspects of a user-defined bio-transport system as a function of both time and position within the system. More specifically, the present invention applies finite-element techniques along with first principles and empirical relationships to a bio-transport system to construct mathematical representations of one or more bio-transport dynamics in and around the bio-transport system based on user-characterized elements representing the bio-transport system. By using a finite-element approach, the bio-transport system can be compartmentalized to manage its intricacies and provide sophisticated bio-transport dynamic data not only as a function of time, but also as a function of the spatial position locating each element defined.
By combining a configurable finite element approach with modern techniques in computer programming and current computer architecture, the present invention creates a simulation model that affords the flexibility and scope needed to address many of the complexities outlined by Lighthill by offering one or more of the following functional capabilities:
(1) Configurable to provide detailed solutions as a function time and at least one space dimension (e.g. axial position along the blood vessels);
(2) Configurable to account for both nonlinear effects (e.g. vessel elasticity and/or conditions of state dependency) and non-Newtonian fluid behavior;
(3) Configurable to represent multi-level branching;
(4) Provides a platform that is readily extendable to cover (a) various bio-transport dynamics phenomena in a bio-transport system such as fluid behavior, chemical, biological, thermal and gravitational/inertial effects, (b) entities that interact with a bio-transport system such as organs and (c) physiological phenomena, effectuated via systems other than bio-transport systems [e.g. the central nervous system], which influence the bio-transport dynamics behavior of a bio-transport system;
(5) Offers an open architecture to permit concurrent, inter=operability with complementary models (e.g. existing organ models);
(6) Harmonizes with modern computer programming paradigms and infrastructure (e.g. with respect to parallel processing, object oriented programming and Imaging and Visualization); and
(7) Extensible to approximate continuity of time and space to any desired degree, within the constraints of computational power and storage access available.
The simulation model of the present invention enables a user to make decisions regarding the configuration of a bio-transport system and to see the effects of these decisions on a system""s bio-transport dynamics, such as, for example, fluid flow rates, pressure gradients, chemical and biological concentrations and fluid temperatures, at various points in time and space. The simulator may be used as an instructional tool to illustrate, for example, the behavior of a representative circulatory system. Additionally, it may be used with respect to a specific bio-transport system as a planning guide to examine alternative strategies to correct problems, or as an experimental platform to elucidate mechanisms occurring in classes of circulatory systems for example. Since it is only a simulator, the user can learn, teach, plan, diagnose or experiment without risk to sentient organisms and in ways that are not ethically and/or technically possible with live organisms.
One aspect of the invention is a method of simulating bio-transport dynamics of a bio-transport system using the configurable simulation model. In practice, computer simulation of a bio-transport system involves two basic steps: (a) constructing a simulation model of a bio-transport system of an organism; and (b) simulating the behavior of the bio-transport system by running the simulation model on a computer. It should be obvious to those skilled in the art that the simulation model must be constructed before it can be run, and that, once constructed, it can be run repeatedly without being xe2x80x9creconstructed.xe2x80x9d Consequently, these steps may be performed jointly or individually.
In a preferred embodiment of the construction phase, a user defines and characterizes elements and one or more transported entities associated therewith to represent the initial state of one of the organism""s bio-transport systems or a portion thereof. A transported entity may be, for example, fluid, energy, chemicals, and biologicals. The term xe2x80x9cfluidxe2x80x9d is used broadly herein and refers to any material capable of flowing and includes, but is not limited to, traditional fluids such as liquids and gases, plus mixtures, dispersions, suspensions or slurries of solid and viscoelastic materials. Examples of fluids include blood, food, and air.
Based on the characterization of the elements, one or more mathematical representations that model particular bio-transport dynamics are constructed for each element. This forms a configured bio-transport system simulation model which has a mathematical representation for particular bio-transport dynamics phenomena at each element of the bio-transport system being modeled. It is especially convenient to designate an object for each element in an object-oriented programming environment, although the present invention is not limited to object-orientated programming techniques.
In a preferred embodiment of the simulation phase, a conventional simulator uploads the configured simulation model, initial conditions are entered, and then the mathematical representations are executed by the simulator for a desired period of time to obtain bio-transport dynamics data at each element as a function of time.
The degree to which one defines and characterizes the elements representing the bio-transport system depends upon the bio-transport dynamics and the specificity desired which may be determined by one skilled in the art. Generally, an element is characterized in terms of its geometry and physical characteristics which may include, for example, shape, dimensions, orientation, elasticity, permeability and resistance to flow, just to name a few. The fluid associated with the element is characterized generally in terms of physical properties such as, for example, viscosity, heat capacity and density, just to name a few. In the preferred embodiment, the model is adapted to handle characteristics which are dependent on xe2x80x9cconditions of state,xe2x80x9d meaning that the characteristics"" values are dependent upon other conditions existent at a particular element. For example, viscosity may be dependent upon temperature of the element""s associated fluid, and an element""s dimensions may be dependent upon the pressure of the element""s associated fluid. The term xe2x80x9cassociated fluidxe2x80x9d as used herein refers to the fluid contained within an element at a particular point in time.
Rather than defining and characterizing an element only as a flow channel component in a bio-transport system, it may be preferable to define an element to include entities that are not only flow channel components of the bio-transport system but also may interact in a special way with the system, such as an organ or a tumor. An element characterized to represent such an entity would model it in an average or xe2x80x9cbulkxe2x80x9d manner such that detailed information with regard to spatial dependence within say an organ would not be available. Thus, for example, an organ may be modeled as an xe2x80x9corgan elementxe2x80x9d and characterized generally with a certain resistance to flow and a certain volumetric capacity, which perhaps is altered by pressure. However, in addition to normal element properties, the organ element may have special properties, such as volumetric pumping rates in a heart organ element, or hormone production in the case of the hypothalamus to mention just a few.
In a preferred embodiment, certain data characterizing elements of a particular bio-transport system are automatically generated by an imaging device such as magnetic resonance imaging (MRI), Computer tomography (CT) or ultrasound. The data generated from these devices then are inputted into the simulation model to construct a simulation model having elements representing the imaged bio-transport system, said configuration possibly being manually adjusted to compensate for any limitations in a totally automated process. The structural arrangement of the computational code effecting this construction preferably is adapted to readily receive the standard format of the input data from the imaging device. Using data from imaging devices is particularly useful in clinical circumstances where the physician/surgeon needs to analyze the unique bio-transport system of a specific patient.
The mathematical constructs are based on known relationships between user-specified characteristics to provide a prediction of bio-transport dynamics. Most bio-transport dynamics are governed by established first principles and physical relationships, for example, conservation of mass, conservation of momentum, conservation of energy, constitutive equations and other empirical relationships. The simulation model uses these relationships along with the user-specified characteristics to calculate bio-transport dynamics aspects such as flow rates, concentrations and pressures at different points in the configured simulation model at different points in time. The results are dependent on how the simulator is configured by the user, so any number of different bio-transport systems may be modeled for different organisms or different parts thereof. It should be understood that the formulae presented herein are to predict behavior and interaction and are not intended to describe or theorize bio-transport dynamics. In other words, the invention does not depend on the theoretical merit of a particular equation providing that it predicts conditions as accurately and precisely as desired by at least one user. It is anticipated that alternative equations may be used to progressively improve the predictive ability and speed of convergence of the simulator as desired by other users.
The particular bio-transport dynamics modeled depend upon the user""s preference although bio-transport simulations in one form or another generally model flow behavior since most bio-transport dynamics, such as dispersion of a chemical or biological component, relate to the fluid flow in the bio-transport system. In a preferred embodiment, to enhance realism and predictability, the simulation model further comprises one or more of the following bio-transport dynamics in addition to fluid behavior: (a) mass transport and reactions of chemicals and other entities, such as viruses, bacteria and clots, in the fluid; (b) heat transport in the fluid including its effects and Transport; (c) external dynamical and mechanical effects such as gravitational and inertial forces, and (d) interaction of elements/organs with other elements/organs that are effectuated by systems outside the bio-transport system under study [for example, effects at a distance produced by the central nervous system when the circulatory system is under study]. This last enhancement provides for user definition of mathematical relationships among variables to represent physiological interactions that exist within an organism, but are not effectuated by bio-transport mechanisms within the bio-transport system being simulated. In addition to modeling for these bio-transport dynamics, the simulator of the present invention may be enhanced with other models as applications dictate.
In a preferred embodiment, the simulation model has an open architecture to permit concurrent, interoperability with complementary models. Such a feature is particularly useful in enabling organ simulators to be networked to provide for more realistic simulations. Since organs are connected by the circulatory system, to model the behavior of an organ in situ, an organ simulator also should be able to simulate the circulatory system through which it communicates chemically and biologically with the rest of the organism and with certain extra-circulatory functional interactions, such as the central nervous system. In addition to providing a common platform to network organs, the simulation model of the present invention provides an open interface for interconnection among various organ models. This saves developers of organ simulators the effort of individually constructing an ancillary circulatory simulator with extra-circulatory functional interactions for each organ model. Additionally, groups of organ developers can leverage on one another""s modeling efforts by jointly using the interface provided by the present invention over remote connections, such as the Internet. Thus, the simulation model of the present invention constitutes a global platform for collaborative research on physiological processes of organisms.
In addition to configuring the simulation model of the present invention as an inter-organ transport model, it may configured as an intra-organ, intra-tissue or intra-cell transport model. In other words, the configurability of the simulation model of the present invention also enables it to simulate fluid flow and transport within an organ, tissue or cell. With respect to organs, flow and transport phenomena underlie the basic behavior of many organs. At least one organ has already been modeled in a fashion to approximate a time-space continuum, for example, in Winslow, R. et.al xe2x80x9cSimulating Cardiac Sinus and Atrial Network Dynamics on the Connection Machinexe2x80x9d Physica D 64 pp281-298, 1993. Likewise, with respect to cells, Tomita, M. et.al. xe2x80x9cE-CELL: Software Environment for Whole Cell Simulationxe2x80x9d Bio. Mag. Keio 1996 describes an xe2x80x9cE-CELL simulatorxe2x80x9d that emulates transcription, translation and other chemical reactions occurring in the cell. Cell modeling, as described in that paper, would be enhanced by the inclusion of fluid flow, chemical/biological and thermal transport phenomena and possibly dynamic effects. Instead of repeating the effort of creating a bio-transport simulator bound to a specific organ, tissue or cell model for each organ, tissue and cell respectively, the simulation model of the present invention, with its ability to be configured and its open architecture, can be used as the bio-transport simulator component in any organ, tissue or cell model, thereby relieving the model developer of the task of managing the bio-transport part of the organ, tissue or cell simulation. Thus, the bio-transport simulation model becomes a simple xe2x80x9cbio-transport objectxe2x80x9d in a modem object-oriented programming environment, or its equivalent in a more-traditional programming environment. It is anticipated that the use of this bio-transport object will accelerate the development of new physiological models and leverage many existing ordinary differential equation [ODE] models of physiological processes by reducing the effort to incorporate true spatial representations using partial differential equations [PDE] into the models.
Another aspect of the invention involves an apparatus for simulating a bio-transport system. In a preferred embodiment, the apparatus comprises (a) a processor; (b) a user interface operatively connected to the processor for receiving input from and conveying output to a user; and (c) memory operatively connected to the processor and containing instructions for constructing and/or executing the simulation model as described above. Preferably, the user interface prompts the user in a logical fashion to define and characterize the elements to represent the transport system to the desired precision/accuracy. Additionally, the user interface preferably displays output in a natural fashion so that the user can intuitively interpret results, thereby reducing errors and increasing acceptability. To this end, it is preferable to employ a structural arrangement of computational code that harmonizes with the natural display of results.
Yet another aspect of the present invention is a computer-readable medium of instructions for enabling the system described above to construct and/or execute the simulation model as described above.